A Simple dashboard

Welcome to the First Interactive Dashboard.

Trend Over Time

p_bar <- gapminder %>%
  filter(year >= 1990) %>%  # Keep only years from 1990 onward
  group_by(year, continent) %>%
  summarize(lifeExp = mean(lifeExp), .groups = "drop") %>%
  ggplot(aes(x = factor(year), y = lifeExp, fill = continent)) +
  geom_col(position = "dodge") +
  labs(title = "Average Life Expectancy by Continent (1990+)",
       x = "Year",
       y = "Life Expectancy",
       fill = "Continent") +
  theme_bw()

plotly::ggplotly(p_bar)

Distribution

data <- gapminder  
g <- ggplot(data, aes(x = lifeExp, fill = factor(year))) +
  geom_histogram(binwidth = 2, alpha = 0.6, position = "identity") +
  labs(title = "Histogram of Life Expectancy by Year",
       x = "Life Expectancy",
       y = "Count",
       fill = "Year") +
  theme_minimal()
plotly::ggplotly(g)

Scatter Plot

g <- ggplot(data, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point(alpha = 0.6) +
  scale_x_log10() +
  labs(title = "Life Expectancy vs GDP per Capita",
       x = "GDP per Capita (log scale)",
       y = "Life Expectancy",
       color = "Continent") +
  theme_minimal()
plotly::ggplotly(g)